Publications associées à Variational Bayesian methods

The complexity of quantum support vector machines

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

Wien2024

Robust Outlier Rejection for 3D Registration with Variational Bayes

Mathieu Salzmann, Jiancheng Yang, Zheng Dang, Zhen Wei, Haobo Jiang

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

Los Alamitos2023

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Laurent Valentin Jospin, Jesse Ray Murray Lahaye

Bayesian statistics is concerned with the integration of new information obtained through observations with prior knowledge, and accordingly, is often related to information theory (Jospin 2022). Recursive Bayesian estimation methods, such as Kalman Filter ...

2023

Preliminary design of the cold mass supports for the EU DEMO feeders

Kamil Sedlák, Roberto Guarino

The Cold Mass Support (CMS) is a basic structural component of the feeder system of the EU DEMO tokamak. The function of this structural element is not only to provide support to the containment duct - wiring the cryogenic lines, electrical bus bars and in ...

ELSEVIER SCIENCE SA2023

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

Camille Roland Marie Minaudo

Elevated nitrate from human activity causes ecosystem and economic harm globally. The factors that control the spatiotemporal dynamics of riverine nitrate concentration remain difficult to describe and predict. We analyzed nitrate concentration from 4450 s ...

SPRINGER2022

Information-driven transitions in projections of underdamped dynamics

Daniel Maria Busiello, Giorgio Nicoletti, Amos Maritan

Low-dimensional representations of underdamped systems often provide useful insights and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spa ...

AMER PHYSICAL SOC2022

Contextually Plausible and Diverse 3D Human Motion Prediction

Mathieu Salzmann, Fatemehsadat Saleh

We tackle the task of diverse 3D human motion prediction, that is, forecasting multiple plausible future 3D poses given a sequence of observed 3D poses. In this context, a popular approach consists of using a Conditional Variational Autoencoder (CVAE). How ...

IEEE2021

Learning in Volatile Environments With the Bayes Factor Surprise

Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi, Vasiliki Liakoni

Surprise-based learning allows agents to rapidly adapt to nonstationary stochastic environments characterized by sudden changes. We show that exact Bayesian inference in a hierarchical model gives rise to a surprise-modulated trade-off between forgetting o ...

MIT PRESS2021

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Variational Bayesian methods

The complexity of quantum support vector machines

Robust Outlier Rejection for 3D Registration with Variational Bayes

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Preliminary design of the cold mass supports for the EU DEMO feeders

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

Information-driven transitions in projections of underdamped dynamics

Contextually Plausible and Diverse 3D Human Motion Prediction

Learning in Volatile Environments With the Bayes Factor Surprise

Learning Self-Exciting Temporal Point Processes Under Noisy Observations

Graph Chatbot

Chattez avec Graph Search

Robust Outlier Rejection for 3D Registration with Variational Bayes

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Preliminary design of the cold mass supports for the EU DEMO feeders

The complexity of quantum support vector machines

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

Information-driven transitions in projections of underdamped dynamics

Contextually Plausible and Diverse 3D Human Motion Prediction

Learning in Volatile Environments With the Bayes Factor Surprise

Learning Self-Exciting Temporal Point Processes Under Noisy Observations